• Journal of Power Electronics
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• v.18 no.3
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• pp.826-840
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• 2018

This paper presents a distributed maximum power point tracking (DMPPT) algorithm based on the reference voltage perturbation (RVP) method for the PV modules of a series PV string. The proposed RVP-DMPPT algorithm is developed to accurately track the maximum power point (MPP) for each PV module operating under all atmospheric conditions with a reduced hardware overhead. To study the influence of parameters such as the controller reference voltage ($V_{ref}$) and PV current ($I_{pv}$) on the PV string voltage, a small signal model of a unidirectional differential power processing (DPP) based PV-Bus architecture is developed. The steady state and dynamic performances of the proposed RVP DMPPT algorithm and small signal model of the unidirectional DPP based PV-Bus architecture are demonstrated with simulations and experimental results. The accuracy of the RVP DMPPT algorithm is demonstrated by obtaining a tracking efficiency of 99.4% from the experiment.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1248-1258
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• 2019

This paper presents a moth-flame optimization (MFO)-based maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The MFO algorithm is a new optimization method that exhibits satisfactory performance in terms of exploration, exploitation, local optima avoidance, and convergence. Therefore, the MFO algorithm is quite suitable for solving multiple peaks of PV systems under partial shading conditions (PSCs). The proposed MFO-MPPT is compared with four MPPT algorithms, namely the perturb and observe (P&O)-MPPT, incremental conductance (INC)-MPPT, particle swarm optimization (PSO)-MPPT and whale optimization algorithm (WOA)-MPPT. Simulation and experiment results demonstrate that the proposed algorithm can extract the global maximum power point (MPP) with greater tracking speed and accuracy under various conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1075-1082
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• 2010

This paper analyzes a operating characteristic for maximum power point tracking (MPPT) of photovoltaic generation system. MPPT methods are used to maximize PV array output power by tracking maximum power point(MPP) continuously. To increase the output efficiency of PV system, it is important to have more efficient MPPT. MPPT algorithm is widely used the control method such as the perturbation and observation(PO) method, incremental conductance(IC) method and constant voltage(CV) method. In case of the radiation is changed, this paper proposes a response characteristic with MPPT control algorithms. Also, it proposes the direct for a novel MPPT control algorithm development through the analyzed data, hereby proves the effectiveness of this paper.

• Journal of Power Electronics
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• v.16 no.1
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• pp.287-296
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• 2016

Conventional maximum power point tracking (MPPT) methods are ineffective under partially shaded conditions because multiple local maximum can be exhibited on power-voltage characteristic curve. This study proposes an improved cuckoo search (ICS) MPPT method after investigating the cuckoo search (CS) algorithm applied in solving multiple MPPT. The algorithm eliminates the random step in the original CS algorithm, and the conception of low-power, high-power, normal and marked zones are introduced. The adaptive step adjustment is also realized according to the different stages of the nest position. This algorithm adopts the large step in low-power and marked zones to reduce search time, and a small step in high-power zone is used to improve search accuracy. Finally, simulation and experiment results indicate that the promoted ICS algorithm can immediately and accurately track the global maximum under partially shaded conditions, and the array output efficiency can be improved.

• Journal of Power Electronics
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• v.12 no.1
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• pp.164-171
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• 2012

Variable step size maximum power point trackers (MPPTs) are widely used in photovoltaic (PV) systems to extract the peak array power which depends on solar irradiation and array temperature. One essential factor which judges system dynamics and steady state performances is the scaling factor (N), which is used to update the controlling equation in the tracking algorithm to determine a new duty cycle. This paper proposes a novel stability study of variable step size incremental resistance maximum power point tracking (INR MPPT). The main contribution of this analysis appears when developing the overall small signal model of the PV system. Therefore, by using linear control theory, the boundary value of the scaling factor can be determined. The theoretical analysis and the design principle of the proposed stability analysis have been validated using MATLAB simulations, and experimentally using a fixed point digital signal processor (TMS320F2808).

• Journal of Power Electronics
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• v.18 no.6
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• pp.1805-1818
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• 2018

This paper proposes a novel hybrid maximum power point tracking (MPPT) algorithm combining a Whale Optimization Algorithm (WOA) and the conventional Perturb & Observation (P&O) to track/extract the highest amount of power from a solar photovoltaic (SPV) system working under partial shading conditions (PSCs). The proposed hybrid algorithm is based on a WOA which predicts the initial global peak (GP) and is followed by P&O in the final stage to achieve a quicker convergence to a GP. Thus, this hybrid algorithm overcomes the computational burden encountered in a standalone WOA, grey wolf optimization (GWO) and hybrid GWO reported in the literature. The conventional algorithm searches for the maximum power point (MPP) in the predicted region by the WOA. The proposed MPPT technique is modelled and simulated using MATLAB/Simulink for simulating an environment to check its effectiveness in accurately tracking the MPP during the GP region. This hybrid algorithm is compared with a standalone WOA, GWO and hybrid GWO. From the simulating results, it is shown that the proposed algorithm offers high tracking performance and that it increases the output power level of a SPV system under partial shading. The algorithm also verified experimentally on various PSCs.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.382-383
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• 2018

To increase the efficiency of a wind energy conversion system (WECS), the maximum power point tracking (MPPT) algorithm is usually employed. This paper proposes an optimal MPPT algorithm which tracks a sudden wind speed change condition fast. The proposed method can be implemented without the prior information on the wind turbine parameters, generator parameters, air density or wind speed. By investigating the directions of changes of the mechanical output power in wind turbine and rotor speed of the generator, the proposed MPPT algorithm is able to determine an optimal speed to achieve the maximum power point. Then, this optimal speed is set to the reference of the speed control loop. As a result, the proposed MPPT algorithm forces the system to operate at the maximum power point by using a three-phase converter. The simulation results based on the PSIM are given to prove the effectiveness of the proposed method.

• ETRI Journal
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• v.33 no.6
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• pp.973-976
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• 2011

This letter describes an efficient technique for maximum power point tracking (MPPT) of an energy harvesting device. It is based on controlling the device voltage at the point of maximum power. Using a microcontroller with a power saving technique, the MPPT algorithm maintains the maximum power with low power consumption. An experiment shows that the algorithm maximizes the energy transfer power using an energy management IC fabricated in a 0.18-${\mu}m$ process. Compared to direct energy transfer to a battery, the proposed technique is more efficient for low-energy harvesting under variable conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1968-1975
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• 2009

The paper proposes a novel control algorithm for tracking maximum power of PV generation system.. The maximum power of PV array is determinated by a insolation and temperature. Prior considered the term in PV generation system is how maximum power point(MPP) is accurately tracked.. The paper proposes a fuzzy neural network(FNN) control algorithm so as to accurately track those maximum power points. The proposed control algorithm comprises the antecedence part of fuzzy rule and clustering method, multi-layer neural network in the consequent part. FNN has the advantages which are depicted both high performance and robustness in fuzzy control and high adaptive control in neural network.. Specially, it can show the outstanding control performance for parameter variations appling to non-linear character of PV array. In this paper, the tracking speed and the accuracy prove the validity through comparing a proposed algorithm with a conventional one.

• KIEAE Journal
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• v.14 no.2
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• pp.21-28
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• 2014

This paper provides the up to date review of the shading effects on PV module performance and the associated detection algorithm related to the maximum power point tracking. It includes the brief explanations of the MMP variations due to the shading occurrence on the PV modules. Review of experimental and simulation studies highlighting the significant impacts of shading on PV efficiencies were presented. The literature indicates that even the partial shading of a single cell can greatly drop the entire module voltage and power efficiency. The MMP tracking approaches were also reviewed in this study. Both conventional and advanced soft computing methods such as ANN, FLC and EA were described for the proper tracking of MMP under shaded conditions. This paper would be the basic source and the comprehensive information associated with the shading effects and relevant MPP tracking technique.